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Hybrid of Lamda and Bee Colony Optimization for Solving Economic Dispatch DOI:10.15199/48.2016.09.54

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This paper proposes the method to solve the economic dispatch problem with hybrid of lamda and bee colony optimization (HLBCO). The fundamental constraints of economic dispatch problem are the load demand and power loss into consideration. The generation cost function considering smooth cost function characteristic. To verify the performance of the proposed HLBCO algorithm, it is operated by the simulation on the MATLAB program and tested the two case studies. The simulation results indicate that the HLBCO can provide a better solution than the others in terms of quality solution, computational and convergence efficiently. Streszczenie. W artykule zapropponowano metode optymalizacji rozsyłu energii prze wykorzystanie hybrydy dwóch metod: lamda i algorytmów rojowych HLBCO. Symulacja przeprowadzona nakilku przykładach dowodzi że zaproponowany algorytm lepiej rozwiązuje prtoblemy ekonomicznego rozsyłu biorąc pod uwagę jakość I skuteczność. Optymalizacja ekonomii rozsyłu enegii z wykorzystaniem metod rojowych I metody lamda.. Keywords: lamda, bee colony, optimization, economic dispatch. Słowa kluczowe: metody rojowe, metoda lamda, optymalizacja rozsyłu enrgii. Introduction The electricity is an important for economic and social development. Planning, security and reliability of electrical power are necessary for electrical power generation. Economic dispatch is the method of determinative the most efficient, low cost and reliable operation of a power. The objective function of economic dispatch is to minimize the total fuel cost of electrical power generation which the demand, power loss and constraints are satisfied. There are many methods to solving the economic dispatch problem. The conventional methods for solving economic dispatch problem are lamda iteration method, gradient method, newton’s method, piecewise linear cost functions and dynamic programming [1] that owing to tedious calculations and its incapability to solve mu[...]

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